def plot_histograms(self,
column='r',
primary_dim=None,
filename=None,
**kwargs):
"""Plot a histograms for all frequencies of one data column
Parameters
----------
column : str, optional
data column to plot. defaults to "r" for resistance
primary_dim : None|str
???
filename : None|str
Prefix for filename. Do not add a file ending here, as additional
string will be appended here.
**kwargs : dict
???
TODO: Check saving to file for more than one secondary dimension
Parameters
----------
"""
dict_dimension, figs = HS.plot_histograms_extra_dims(
self.data, column, primary_dim, **kwargs)
if filename is not None:
for key, item in figs.items():
item.savefig(filename +
'_{}.jpg'.format(key).replace('_', '-'),
dpi=300)
return dict_dimension, figs
# ## Histogram plotting
# In[13]:
obj.data.dtypes
# In[14]:
import reda.plotters.histograms as RH
fig = RH.plot_histograms_extra_dims(
obj,
keys=[
'rho_a',
],
extra_dims=[
'timestep',
],
Nx=5,
#subquery='timestep in {0}'.format(list(range(0, 100, 10))),
subquery='timestep in [0, 3, 6]')
# print(fig.get_figwidth(), fig.get_figheight())
# fig.savefig('histogram.png', dpi=300)
# ## Plotting Pseudosections
# In[15]:
import reda.plotters.pseudoplots as PS
fig = PS.plot_ps_extra(obj, 'rho_a', subquery='timestep in [0, 3, 6]')
import glob
filenames = sorted(glob.glob('data/pygimli_*.ohm'))
for nr, filename in enumerate(filenames):
obj.import_bert(filename, timestep=nr)
obj.compute_K_analytical(spacing=1)
# import reda.utils.norrec as NR
# NR.assign_norrec_to_df(obj.data)
import reda.plotters.histograms as RH
results = RH.plot_histograms_extra_dims(
obj,
keys=['rho_a'],
extra_dims=[
'timestep',
],
Nx=5,
)
results.tight_layout()
results.savefig('histogram.png', dpi=300)
exit()
import IPython
IPython.embed()
exit()
# import IPython
# IPython.embed()
for key, item in results.items():
item['all'].savefig('hist_{0}.png'.format(key), dpi=300)